Overview

Dataset statistics

Number of variables9
Number of observations74
Missing cells70
Missing cells (%)10.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory74.7 B

Variable types

Numeric1
Categorical3
Text4
DateTime1

Dataset

Description전북특별자치도 장사정보 시설 현황에 관한 데이터입니다. (시군, 구분, 종류, 명칭, 위치, 전화번호, 영업개시일, 비고 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/15045442/fileData.do

Alerts

연번 is highly overall correlated with 시군High correlation
시군 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 시군High correlation
구분 is highly imbalanced (69.7%)Imbalance
비고 has 70 (94.6%) missing valuesMissing
위치 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 11:30:57.700463
Analysis finished2024-03-14 11:30:59.526970
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct73
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.527027
Minimum1
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size794.0 B
2024-03-14T20:30:59.727877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.65
Q119.25
median37.5
Q355.75
95-th percentile70.35
Maximum74
Range73
Interquartile range (IQR)36.5

Descriptive statistics

Standard deviation21.497514
Coefficient of variation (CV)0.57285416
Kurtosis-1.1971702
Mean37.527027
Median Absolute Deviation (MAD)18.5
Skewness-0.003514341
Sum2777
Variance462.1431
MonotonicityIncreasing
2024-03-14T20:31:00.180347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32 2
 
2.7%
1 1
 
1.4%
49 1
 
1.4%
55 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
48 1
 
1.4%
Other values (63) 63
85.1%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
74 1
1.4%
73 1
1.4%
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%

시군
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size720.0 B
전주시
17 
익산시
10 
정읍시
9 
군산시
7 
남원시
5 
Other values (9)
26 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)2.7%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row전주시
5th row전주시

Common Values

ValueCountFrequency (%)
전주시 17
23.0%
익산시 10
13.5%
정읍시 9
12.2%
군산시 7
9.5%
남원시 5
 
6.8%
순창군 5
 
6.8%
김제시 4
 
5.4%
고창군 4
 
5.4%
완주군 3
 
4.1%
임실군 3
 
4.1%
Other values (4) 7
9.5%

Length

2024-03-14T20:31:00.611789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 17
23.0%
익산시 10
13.5%
정읍시 9
12.2%
군산시 7
9.5%
남원시 5
 
6.8%
순창군 5
 
6.8%
김제시 4
 
5.4%
고창군 4
 
5.4%
완주군 3
 
4.1%
임실군 3
 
4.1%
Other values (4) 7
9.5%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size720.0 B
사설
70 
공설
 
4

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사설
2nd row사설
3rd row사설
4th row사설
5th row사설

Common Values

ValueCountFrequency (%)
사설 70
94.6%
공설 4
 
5.4%

Length

2024-03-14T20:31:00.994717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:31:01.315280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사설 70
94.6%
공설 4
 
5.4%

종류
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size720.0 B
전문
50 
병원
24 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row병원
2nd row전문
3rd row전문
4th row전문
5th row전문

Common Values

ValueCountFrequency (%)
전문 50
67.6%
병원 24
32.4%

Length

2024-03-14T20:31:01.865336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:31:02.182108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문 50
67.6%
병원 24
32.4%

명칭
Text

Distinct72
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-14T20:31:02.942512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.8108108
Min length6

Characters and Unicode

Total characters578
Distinct characters111
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)94.6%

Sample

1st row전북대학교병원 장례식장
2nd row금성장례식장
3rd row온고을 장례식장
4th row대송장례식장
5th row현대장례식장
ValueCountFrequency (%)
장례식장 3
 
3.8%
호남장례식장 2
 
2.5%
현대장례식장 2
 
2.5%
순창요양병원장례식장 1
 
1.3%
삼봉장례식장 1
 
1.3%
김제중앙병원 1
 
1.3%
김제새만금장례식장 1
 
1.3%
김제장례식장 1
 
1.3%
김제우석병원 1
 
1.3%
봉동호스피스장례식장 1
 
1.3%
Other values (65) 65
82.3%
2024-03-14T20:31:04.182428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 132
22.8%
례 70
 
12.1%
식 60
 
10.4%
원 32
 
5.5%
병 14
 
2.4%
화 8
 
1.4%
문 8
 
1.4%
군 8
 
1.4%
료 7
 
1.2%
의 7
 
1.2%
Other values (101) 232
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 559
96.7%
Close Punctuation 6
 
1.0%
Open Punctuation 6
 
1.0%
Space Separator 5
 
0.9%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 132
23.6%
례 70
 
12.5%
식 60
 
10.7%
원 32
 
5.7%
병 14
 
2.5%
화 8
 
1.4%
문 8
 
1.4%
군 8
 
1.4%
료 7
 
1.3%
의 7
 
1.3%
Other values (96) 213
38.1%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
G 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 559
96.7%
Common 17
 
2.9%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 132
23.6%
례 70
 
12.5%
식 60
 
10.7%
원 32
 
5.7%
병 14
 
2.5%
화 8
 
1.4%
문 8
 
1.4%
군 8
 
1.4%
료 7
 
1.3%
의 7
 
1.3%
Other values (96) 213
38.1%
Common
ValueCountFrequency (%)
) 6
35.3%
( 6
35.3%
5
29.4%
Latin
ValueCountFrequency (%)
M 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 559
96.7%
ASCII 19
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 132
23.6%
례 70
 
12.5%
식 60
 
10.7%
원 32
 
5.7%
병 14
 
2.5%
화 8
 
1.4%
문 8
 
1.4%
군 8
 
1.4%
료 7
 
1.3%
의 7
 
1.3%
Other values (96) 213
38.1%
ASCII
ValueCountFrequency (%)
) 6
31.6%
( 6
31.6%
5
26.3%
M 1
 
5.3%
G 1
 
5.3%

위치
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-14T20:31:05.419791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13.5
Mean length10.554054
Min length5

Characters and Unicode

Total characters781
Distinct characters126
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row덕진구 건지로 20
2nd row덕진구 가리내로 670
3rd row덕진구 온고을 438-2
4th row덕진구 동부대로 1015
5th row덕진구 초포다리로 64
ValueCountFrequency (%)
완산구 9
 
4.7%
덕진구 8
 
4.1%
순창읍 5
 
2.6%
무왕로 3
 
1.6%
충정로 3
 
1.6%
고창읍 3
 
1.6%
녹두로 2
 
1.0%
14 2
 
1.0%
94 2
 
1.0%
진안읍 2
 
1.0%
Other values (144) 154
79.8%
2024-03-14T20:31:07.092414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
 
15.2%
로 57
 
7.3%
1 47
 
6.0%
2 31
 
4.0%
5 28
 
3.6%
3 27
 
3.5%
6 26
 
3.3%
4 26
 
3.3%
7 22
 
2.8%
- 20
 
2.6%
Other values (116) 378
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 386
49.4%
Decimal Number 252
32.3%
Space Separator 119
 
15.2%
Dash Punctuation 20
 
2.6%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 57
 
14.8%
읍 20
 
5.2%
구 19
 
4.9%
동 17
 
4.4%
산 13
 
3.4%
진 12
 
3.1%
덕 11
 
2.8%
완 10
 
2.6%
창 10
 
2.6%
면 8
 
2.1%
Other values (102) 209
54.1%
Decimal Number
ValueCountFrequency (%)
1 47
18.7%
2 31
12.3%
5 28
11.1%
3 27
10.7%
6 26
10.3%
4 26
10.3%
7 22
8.7%
0 19
7.5%
9 16
 
6.3%
8 10
 
4.0%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 395
50.6%
Hangul 386
49.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 57
 
14.8%
읍 20
 
5.2%
구 19
 
4.9%
동 17
 
4.4%
산 13
 
3.4%
진 12
 
3.1%
덕 11
 
2.8%
완 10
 
2.6%
창 10
 
2.6%
면 8
 
2.1%
Other values (102) 209
54.1%
Common
ValueCountFrequency (%)
119
30.1%
1 47
 
11.9%
2 31
 
7.8%
5 28
 
7.1%
3 27
 
6.8%
6 26
 
6.6%
4 26
 
6.6%
7 22
 
5.6%
- 20
 
5.1%
0 19
 
4.8%
Other values (4) 30
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 395
50.6%
Hangul 386
49.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
30.1%
1 47
 
11.9%
2 31
 
7.8%
5 28
 
7.1%
3 27
 
6.8%
6 26
 
6.6%
4 26
 
6.6%
7 22
 
5.6%
- 20
 
5.1%
0 19
 
4.8%
Other values (4) 30
 
7.6%
Hangul
ValueCountFrequency (%)
로 57
 
14.8%
읍 20
 
5.2%
구 19
 
4.9%
동 17
 
4.4%
산 13
 
3.4%
진 12
 
3.1%
덕 11
 
2.8%
완 10
 
2.6%
창 10
 
2.6%
면 8
 
2.1%
Other values (102) 209
54.1%

전화번호
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-14T20:31:08.208117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters592
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row250-1439
2nd row276-4444
3rd row211-5000
4th row274-4300
5th row275-4444
ValueCountFrequency (%)
250-1439 1
 
1.4%
261-4445 1
 
1.4%
263-4464 1
 
1.4%
548-8844 1
 
1.4%
545-0033 1
 
1.4%
548-4700 1
 
1.4%
540-5184 1
 
1.4%
632-4440 1
 
1.4%
632-9400 1
 
1.4%
620-1306 1
 
1.4%
Other values (64) 64
86.5%
2024-03-14T20:31:09.700255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 184
31.1%
- 74
12.5%
0 54
 
9.1%
5 49
 
8.3%
3 48
 
8.1%
2 42
 
7.1%
6 40
 
6.8%
8 37
 
6.2%
1 33
 
5.6%
7 18
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 518
87.5%
Dash Punctuation 74
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 184
35.5%
0 54
 
10.4%
5 49
 
9.5%
3 48
 
9.3%
2 42
 
8.1%
6 40
 
7.7%
8 37
 
7.1%
1 33
 
6.4%
7 18
 
3.5%
9 13
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 592
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 184
31.1%
- 74
12.5%
0 54
 
9.1%
5 49
 
8.3%
3 48
 
8.1%
2 42
 
7.1%
6 40
 
6.8%
8 37
 
6.2%
1 33
 
5.6%
7 18
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 184
31.1%
- 74
12.5%
0 54
 
9.1%
5 49
 
8.3%
3 48
 
8.1%
2 42
 
7.1%
6 40
 
6.8%
8 37
 
6.2%
1 33
 
5.6%
7 18
 
3.0%

영업개시일
Date

Distinct71
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size720.0 B
Minimum1993-06-28 00:00:00
Maximum2018-11-13 00:00:00
2024-03-14T20:31:10.102902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:31:10.481324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

비고
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing70
Missing (%)94.6%
Memory size720.0 B
2024-03-14T20:31:10.830668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st row폐업
2nd row휴업
3rd row휴업
4th row휴업
ValueCountFrequency (%)
휴업 3
75.0%
폐업 1
 
25.0%
2024-03-14T20:31:11.355436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 4
50.0%
휴 3
37.5%
폐 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 4
50.0%
휴 3
37.5%
폐 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 4
50.0%
휴 3
37.5%
폐 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 4
50.0%
휴 3
37.5%
폐 1
 
12.5%

Interactions

2024-03-14T20:30:58.545076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:31:11.578545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구분종류명칭위치전화번호영업개시일비고
연번1.0000.9300.4870.0000.8831.0001.0000.9481.000
시군0.9301.0000.8780.3260.9271.0001.0000.9371.000
구분0.4870.8781.0000.1581.0001.0001.0001.000NaN
종류0.0000.3260.1581.0001.0001.0001.0000.0000.000
명칭0.8830.9271.0001.0001.0001.0001.0000.9851.000
위치1.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
영업개시일0.9480.9371.0000.0000.9851.0001.0001.0001.000
비고1.0001.000NaN0.0001.0001.0001.0001.0001.000
2024-03-14T20:31:11.783952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군종류구분
시군1.0000.2280.664
종류0.2281.0000.100
구분0.6640.1001.000
2024-03-14T20:31:11.933485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구분종류
연번1.0000.7110.3510.000
시군0.7111.0000.6640.228
구분0.3510.6641.0000.100
종류0.0000.2280.1001.000

Missing values

2024-03-14T20:30:58.915271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:30:59.356990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번시군구분종류명칭위치전화번호영업개시일비고
01전주시사설병원전북대학교병원 장례식장덕진구 건지로 20250-14392000-04-14<NA>
12전주시사설전문금성장례식장덕진구 가리내로 670276-44442003-07-05<NA>
23전주시사설전문온고을 장례식장덕진구 온고을 438-2211-50001995-06-15<NA>
34전주시사설전문대송장례식장덕진구 동부대로 1015274-43002012-02-01<NA>
45전주시사설전문현대장례식장덕진구 초포다리로 64275-44442014-11-26<NA>
56전주시사설전문삼성장례문화원덕진구 동부대로 937247-10032014-10-01<NA>
67전주시사설병원고려병원장례식장덕진구 안덕원로 367242-99442016-07-14<NA>
78전주시사설병원예수병원장례식장완산구 서원로 365285-10091993-06-28<NA>
89전주시사설병원엠마오사랑병원장례식장완산구 서원로 402-35285-44111998-05-23<NA>
910전주시사설전문효자 장례타운완산구 콩쥐팥쥐로 1705-36228-44412013-06-27<NA>
연번시군구분종류명칭위치전화번호영업개시일비고
6465순창군사설전문현대장례식장순창읍 교성로 141-21653-44442004-07-26<NA>
6566순창군사설병원순창요양병원장례식장순창읍 순창로 105653-41232018-10-08<NA>
6667순창군사설전문온누리장례식장순창읍 남계로 14653-44822016-04-04<NA>
6768고창군사설전문새고창장례식장고창읍 고인돌대로 1763563-10012006-05-16<NA>
6869고창군사설전문우리장례식장고창읍 녹두로 1313-6564-33222005-02-28<NA>
6970고창군사설전문고인돌장례식장고창읍 녹두로 1295562-32232003-07-16<NA>
7071고창군사설전문흥덕장례식장흥덕면 고인돌대로 2582-7564-44402005-08-01<NA>
7172부안군사설전문호남장례식장행안면 부안로 2563581-10042011-02-08<NA>
7273부안군사설전문혜성장례식장부안읍 부령로 34584-43002003-10-10<NA>
7374부안군사설병원효요양병원장례식장행안면 염소로 25582-39392006-05-26<NA>